Audio to Video API

An audio to video API uses audio as a driving signal or reference for a generated video. Some workflows animate a speaking portrait; others combine sound with images, text or footage. The selected model determines what the audio controls and which additional inputs are required.

Only if the selected endpoint supports that input combination. Many audio-driven workflows also require a portrait, prompt or visual reference. Check the required fields before submission; an Audio to Video task label does not mean audio alone defines the complete scene.

No. Putting audio over a still image or waveform is a media-rendering task. AI audio-driven generation creates or animates visual content using a model. Decide whether you need a file container change, a speaking portrait or generative visuals before choosing an API.

Start with Talking Avatar models that document portrait and driving-audio inputs. They are designed around a speaking subject. Test lip alignment, facial movement and source-image requirements; a general multimodal video endpoint may use audio without providing the same avatar controls.

Look for a documented music-video or audio-visualization workflow and test how it uses rhythm and structure. General audio-reference support is not a promise of beat synchronization. Music-related tools and multimodal video generation can have different inputs and output behavior.

Use clear audio without clipping, excessive background noise or long irrelevant sections. Confirm the accepted codec, duration, file size and URL requirements. For speech animation, a clean single-speaker sample makes it easier to judge timing and mouth movement.

Yes, when its output format and duration meet the video endpoint requirements. Generate and inspect the narration first, then supply it as driving audio or a supported reference. Keep the text, voice settings and audio asset linked to the video job for later revisions.

No. The endpoint may preserve, reinterpret, condition on or generate audio differently. Check the documentation and listen to the completed clip. If the original track must remain exact, verify the result and plan a separate audio assembly step where needed.

Submit the model with its required audio and visual inputs, then save task_id. Use PoYo status polling or a supported webhook callback to obtain the completed video. Inspect both picture and soundtrack before treating the task as a usable creative result.

Pricing depends on the selected model, quality settings and duration rules. Check whether the tier uses generated seconds, input duration or another billing unit. Compare a realistic example with all required references rather than assuming audio-driven generation has one universal rate.

First confirm that the endpoint is intended for speech synchronization or the timing behavior you need. Then check source audio quality, portrait visibility and supported duration. Compare a short, clean sample before changing several model settings or generating a long clip.

Open the chosen model page for its required audio, image and prompt fields, supported formats and examples. Use its API documentation or model-specific llms.txt when coding. Keep the source assets accessible to the service and track the returned task ID in your application.